Vibration-Controlled Transient Elastography Scores to Predict Liver-Related Events in Steatotic Liver Disease

Importance Metabolic dysfunction–associated steatotic liver disease (MASLD) is currently the most common chronic liver disease worldwide. It is important to develop noninvasive tests to assess the disease severity and prognosis.Objective To study the prognostic implications of baseline levels and dynamic changes of the vibration-controlled transient elastography (VCTE)–based scores developed for the diagnosis of advanced fibrosis (Agile 3+) and cirrhosis (Agile 4) in patients with MASLD.Design, Setting, and Participants This cohort study included data from a natural history cohort of patients with MASLD who underwent VCTE examination at 16 tertiary referral centers in the US, Europe, and Asia from February 2004 to January 2023, of which the data were collected prospectively at 14 centers. Eligible patients were adults aged at least 18 years with hepatic steatosis diagnosed by histologic methods (steatosis in ≥5% of hepatocytes) or imaging studies (ultrasonography, computed tomography or magnetic resonance imaging, or controlled attenuation parameter ≥248 dB/m by VCTE).Main Outcomes and Measures The primary outcome was liver-related events (LREs), defined as hepatocellular carcinoma or hepatic decompensation (ascites, variceal hemorrhage, hepatic encephalopathy, or hepatorenal syndrome), liver transplant, and liver-related deaths. The Agile scores were compared with histologic and 8 other noninvasive tests.Results A total of 16 603 patients underwent VCTE examination at baseline (mean [SD] age, 52.5 [13.7] years; 9600 [57.8%] were male). At a median follow-up of 51.7 (IQR, 25.2-85.2) months, 316 patients (1.9%) developed LREs. Both Agile 3+ and Agile 4 scores classified fewer patients between the low and high cutoffs than most fibrosis scores and achieved the highest discriminatory power in predicting LREs (integrated area under the time-dependent receiver-operating characteristic curve, 0.89). A total of 10 920 patients (65.8%) had repeated VCTE examination at a median interval of 15 (IQR, 11.3-27.7) months and were included in the serial analysis. A total of 81.9% of patients (7208 of 8810) had stable Agile 3+ scores and 92.6% of patients (8163 of 8810) had stable Agile 4 scores (same risk categories at both assessments). The incidence of LREs was 0.6 per 1000 person-years in patients with persistently low Agile 3+ scores and 30.1 per 1000 person-years in patients with persistently high Agile 3+ scores. In patients with high Agile 3+ score at baseline, a decrease in the score by more than 20% was associated with substantial reduction in the risk of LREs. A similar trend was observed for the Agile 4 score, although it missed more LREs in the low-risk group.Conclusions and Relevance Findings of this study suggest that single or serial Agile scores are highly accurate in predicting LREs in patients with MASLD, making them suitable alternatives to liver biopsy in routine clinical practice and in phase 2b and 3 clinical trials for steatohepatitis

Management of hepatitis B virus reactivation due to treatment of COVID-19

The world has made significant progress in developing novel treatments for COVID-19 since the pandemic began. Some treatments target the patient's dysregulated inflammatory response during COVID-19 infection and may cause hepatitis B reactivation (HBVr) in patients with current or past hepatitis B virus (HBV) infection. This review summarizes the risk and management of HBVr due to different treatments of COVID-19 in patients who have current or past HBV infection. Abnormal liver function tests are common during COVID-19 infection. Current evidence suggests that current or past HBV infection is not associated with an increased risk of liver injury and severe disease in COVID-19 patients. Among patients who received high-dose corticosteroids, various immunosuppressive monoclonal antibodies and inhibitors of Janus kinase, the risk of HBVr exists, especially among those without antiviral prophylaxis. Data, however, remain scarce regarding the specific use of immunosuppressive therapies in COVID-19 patients with HBV infection. Some results are mainly extrapolated from patients receiving the same agents in other diseases. HBVr is a potentially life-threatening event following profound immunosuppression by COVID-19 therapies. Future studies should explore the use of immunosuppressive therapies in COVID-19 patients with HBV infection and the impact of antiviral prophylaxis on the risk of HBVr

Statistical strategies for HCC risk prediction models in patients with chronic hepatitis B

Risk prediction modelling for hepatocellular carcinoma (HCC) has been the focus of research in the last decade. The prediction models would help HCC risk stratification, so that patients at high risk of HCC would be able to receive more appropriate management and HCC surveillance. These models were mostly developed in treatment-naïve chronic hepatitis B patients in the early days. In recent years, more prediction models were derived and validated in patients who have received antiviral treatment, which account for the majority of patients who are at increased risk of HCC. Various statistical tests are adopted in developing and validating a risk prediction model - commonly Cox proportional hazards regression, time-dependent receiver operating characteristic (ROC) curve and area under the ROC curve. Even in well-validated models, there may be some pitfalls, e.g., generalizability and clinical applicability. The future direction of prediction model development should be directed towards a more personalised approach. Continuous optimisation of the predictive accuracy of the models would be achieved by involving more serial and dynamic parameters

Non-invasive biomarkers for liver inflammation in non-alcoholic fatty liver disease: present and future

Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease (NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its dynamic nature and poor correlation with liver biochemical markers. Liver histology keeps its role as the standard tool, yet it is well-known for substantial sampling, intraobserver, and interobserver variability. Serum proinflammatory cytokines and apoptotic markers, namely cytokeratin-18, are well-studied with reasonable accuracy, whereas serum metabolomics and lipidomics have been adopted in some commercially available diagnostic models. Ultrasound and computed tomography imaging techniques are attractive due to their wide availability; yet their accuracies may not be comparable with magnetic resonance imaging-based tools. Machine learning and deep learning models, be they supervised or unsupervised learning, are promising tools to identify various subtypes of NAFLD, including those with dominating liver inflammation, contributing to sustainable care pathways for NAFLD

DATA-GRU: Dual-Attention Time-Aware Gated Recurrent Unit for Irregular Multivariate Time Series

Due to the discrepancy of diseases and symptoms, patients usually visit hospitals irregularly and different physiological variables are examined at each visit, producing large amounts of irregular multivariate time series (IMTS) data with missing values and varying intervals. Existing methods process IMTS into regular data so that standard machine learning models can be employed. However, time intervals are usually determined by the status of patients, while missing values are caused by changes in symptoms. Therefore, we propose a novel end-to-end Dual-Attention Time-Aware Gated Recurrent Unit (DATA-GRU) for IMTS to predict the mortality risk of patients. In particular, DATA-GRU is able to: 1) preserve the informative varying intervals by introducing a time-aware structure to directly adjust the influence of the previous status in coordination with the elapsed time, and 2) tackle missing values by proposing a novel dual-attention structure to jointly consider data-quality and medical-knowledge. A novel unreliability-aware attention mechanism is designed to handle the diversity in the reliability of different data, while a new symptom-aware attention mechanism is proposed to extract medical reasons from original clinical records. Extensive experimental results on two real-world datasets demonstrate that DATA-GRU can significantly outperform state-of-the-art methods and provide meaningful clinical interpretation

Reply to Allaire, M.; Thabut, D. Comment on “Wu et al. Baveno VII Criteria Is an Accurate Risk Stratification Tool to Predict High-Risk Varices Requiring Intervention and Hepatic Events in Patients with Advanced Hepatocellular Carcinoma. <i>Cancers</i> 2023, <i>15</i>, 2480”

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Overview of methodologies and statistical strategies in observational studies and meta-analyses on the risk of hepatocellular carcinoma in patients with chronic hepatitis B on entecavir or tenofovir therapy

Entecavir (ETV) and tenofovir disoproxil fumarate (TDF) are first-line antiviral therapies for patients with chronic hepatitis B (CHB) and reduce the risk of disease progression and liver-related complications, as well as improve survival by effectively suppressing viral replication. Nevertheless, since the first publication in 2019 on a lower risk of hepatocellular carcinoma (HCC) in Korean patients receiving TDF than those receiving ETV, the topic has remained a hot and unsettled debate. Multiple studies and meta-analyses have yielded conflicting results. As HCC takes time to develop, studies are mainly observational to benefit from a larger sample size and longer follow-up that provides a higher statistical power to compare the two treatments. However, TDF was available to CHB patients a few years later than ETV in most countries, thus leading to a difference in follow-up duration. Moreover, despite studying the same topic, the difference in data sources and available parameters, inclusion and exclusion criteria, and use of statistical methods complicated the interpretation and comparison of the findings and contributed to between-study heterogeneity in meta-analyses. This review describes some caveats in interpreting and comparing the results from these observational studies and meta-analyses. Future studies should explore better designed observational studies with high-quality data sources, and aggregation of patient data in meta-analysis to tackle between-study heterogeneity